THEME: URBAN DYNAMICS Exploitation of traffic counting data for traffic study in urban areas: from traffic assignment to simulation model validation EMERY Justin
BOYARD-MICHEAU Joseph
MARILLEAU Nicolas
PhD ThèMA/Géobiosphère, CRC, UMR 6049 CNRS/ UMR 6282 CNRS 2, boulevard Gabriel 21000 Dijon (FRANCE)
PhD Géobiosphère, CRC UMR 6282 CNRS 6, boulevard Gabriel 21000 Dijon (FRANCE)
Research Ingineer IRD UR 079 GEODES 32 rue Henri Varagnat 93143 Bondy (FRANCE)
[email protected]
[email protected]
[email protected]
MARTINY Nadége
THEVENIN Thomas
Assistant Professor Géobiosphère, CRC UMR 6282 CNRS 6, boulevard Gabriel 21000 Dijon (FRANCE)
Professor ThèMA UMR 6049 CNRS 2, boulevard Gabriel 21000 Dijon (FRANCE)
[email protected]
[email protected]
ABSTRACT: Background and purpose of the study: Traffic monitoring through the use of automated systems aims at regulating the traffic light cycles and monitoring traffic in urban areas (PREDIT, 2000). These systems transmit real-time traffic flow data in the Regularization Traffic System (RST), which can be called "big data" (Manovich, 2011, Citton, 2012). Since the 60s, urban transport modelling and representation of road traffic have considerably evolved and come to an end in their primary vocation (political infrastructure). This enables to move towards new applications such as the assessment of environmental pollution due to traffic (e.g. noise and air quality) (Debizet, 2011, Fouillé et al, 2012). For instance, the study of nearby atmospheric pollution leads to focus on the actual traffic variability on a relatively short time step (Carslaw et al, 2007, Oxley et al, 2009). In this case, the use of counting data appears appropriate to supply simulation models from an environmental point of view. However, this changing paradigm in urban modelling leads to question the development and the construction of traffic data dedicated to studies of evolution and impact of road traffic at a fine scale in time and space. This point is all the more important that the traffic can never be entirely reconstructed but built within urban
models (Fouillé et al, 2012). Various questions appear as essential: Which use can be made of this data? Which directions can be suggested to assign traffic counts in simulation models? Data and methods The methodology is based on the use of a network of electromagnetic sensors located underground in order to measure the number of cars. These data are used to obtain an image of the road traffic. At a short time step (from the minute to the hour), this system is the most currently to follow the road traffic along the day in French urban areas. The aim of this proposal is to contribute to the use and application of these data following two methodological axes: • The first deals with the structure and statistical processing of traffic counts (test of discrepancy, errors process and spatial validation). This phase is crucial for the reconstruction of missing or inconsistent values from statistical series (PREDIT 2000, Planchon, 2005). Three complementary approaches will be tested: (i) statistical, (ii) spatial and (iii) statistical & spatial. • The second axis aims at inserting the data in a representation model in two ways: first, the assignment of road counts to supply the model, and second, the exploitation of these data to validate, or not, the model outputs. Contribution: Across the case of Dijon city equipped with a network of 210 sensors which have continuously measured the traffic at a 15-minute time step for the 2001-2012 period ; this means 385 440 counts per station. With a two-step modelling process going from the observed data at the modelling data, these analyses appear crucial to open a discussion on the incoming data which represent an important challenge for road impact studies. Especially as traffic data are usually not discussed in terms of their conditions of production and use, which are object of criticism concerning the phenomenon "GIGO" (garbage in, garbage out!) (Fouillé et al, 2012). KEYWORDS: Traffic data, Qualification, Statistical models, Assignment models, Urban Transport Model REFERENCES: 1 Ambrosino G, Sassoli P, Bielli M, Carotenuto P., Romanazzo M., 1999: A modeling
framework for impact assessment of urban transport systems, Transportation Research Part D 4, pp. 73–79 2 Carslaw D. C., Beevers S. D., Bell M. C., 2007, Risks of exceeding the hourly EU limit value for nitrogen dioxide resulting from increased road transport emissions of primary nitrogen dioxide, Atmospheric Environment [En ligne]. mars 2007. Vol. 41, n°10, pp. 2073–2082
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